상세정보
학술대회
Anomaly Detection Algorithm Based on Global Object Map for Video Surveillance System
- 발행일
- 202010
- 출처
- International Conference on Control, Automation and Systems (ICCAS) 2020, pp.1-3
- 협약과제
- 20HS3500, 실외 무인 경비 로봇을 위한 멀티모달 지능형 정보분석 기술 개발, 신호철
- 초록
- Recently, smart video security systems have been active. The existing video security system is mainly a method of detecting a local abnormality of a unit camera. In this case, it is difficult to obtain the characteristics of each local region and the situation for the entire watching area. In this paper, we developed an object map for the entire surveillance area using a combination of surveillance cameras, and developed an algorithm to detect anomalies by learning normal situations. The surveillance camera in each area detects and tracks people and cars, and creates a local object map and transmits it to the server. The surveillance server combines each local maps to generate a global map for entire areas. Probability maps were automatically calculated from the global maps, and normal and abnormal decisions were performed through trained data about normal situations. For three reporting status: normal, caution, and warning, and the caution report performance shows that normal detection 99.99% and abnormal detection 86.6%.
- KSP 제안 키워드
- Anomaly detection algorithm, Smart Video, Video surveillance system, abnormal detection, probability map, security system, surveillance camera, video security